class_docstr: Stacks several observations on top of each other. For image observation this will
  create a 3D blob. The stacking is done in a lazy manner in order to reduce memory consumption. To achieve this,
  a LazyStack object is used in order to wrap the observations in the stack. For this reason, the
  ObservationStackingFilter **must** be the last filter in the inputs filters stack.
  This filter is stateful since it stores the previous step result and depends on it.
  The filter adds an additional dimension to the output observation.
  
  Warning!!! The filter replaces the observation with a LazyStack object, so no filters should be
  applied after this filter. applying more filters will cause the LazyStack object to be converted to a numpy array
  and increase the memory footprint.
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code: def reset(self) -> None:
      self.stack = []
  
file_path: coach/rl_coach/filters/observation/observation_stacking_filter.py
imports: import copy
  from collections import deque
  import numpy
  from rl_coach.core_types import ObservationType
  from rl_coach.filters.observation.observation_filter import ObservationFilter
  from rl_coach.spaces import ObservationSpace, VectorObservationSpace
label_desc: Use image node_id 7 for calling the ObservationStackingFilter obj's underlying member method code with example usage: obj.reset() without return types